Activeloop
Activeloop builds Deep Lake, a database for AI that stores multimodal datasets (text, images, video, audio, embeddings) in a deep-learning-optimized format. The primary interface is the open-source Deep Lake Python SDK paired with the Tensor Query Language (TQL); datasets live locally, in your own cloud (S3, Azure, GCP), or in the managed Activeloop Cloud (app.activeloop.ai), which also exposes an alpha Managed Database REST query endpoint.
APIs
Deep Lake SDK (Python)
The open-source `deeplake` Python package (Apache-2.0) is the primary interface to Deep Lake. It creates, reads, writes, versions, and streams multimodal datasets and embeddings...
Tensor Query Language (TQL)
A high-performance, SQL-like query engine (implemented in C++ inside Deep Lake) for filtering datasets and running hybrid embedding-plus-attribute search. TQL queries are execut...
Deep Lake Vector Store
A multimodal vector store, exposed through the Deep Lake Python SDK (`VectorStore`), that stores embeddings with their metadata and supports similarity and hybrid (TQL) search. ...
Activeloop Managed Database REST API
An alpha REST endpoint for the Managed Tensor Database that accepts a TQL query string over HTTP POST and returns query results. Requires a Bearer `ACTIVELOOP_TOKEN` and a datas...
